Dynamic collaborative optimization for disaster relief supply chains under information ambiguity

Jiaxiang Zhu, Yangyan Shi (), V. G. Venkatesh, Samsul Islam, Zhiping Hou and Sobhan Arisian
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Jiaxiang Zhu: Changzhou University
Yangyan Shi: China University of Geosciences (Wuhan)
V. G. Venkatesh: Metis Lab, EM Normandie Business School
Samsul Islam: Dalhousie University
Zhiping Hou: Guilin University of Technology
Sobhan Arisian: La Trobe University

Annals of Operations Research, 2024, vol. 335, issue 3, No 15, 1303-1329

Abstract: Abstract Large-scale disasters occur worldwide, with a continuing surge in the frequency and severity of disruptive events. Researchers have developed several optimization models to address the critical challenges of disaster relief supply chains (e.g., emergency material reserving and scheduling inefficiencies). However, most developed algorithms are proven to have low fault tolerance, which makes it difficult for disaster relief supply chain managers to obtain optimal solutions and meet the emergency distribution requirements within a limited time frame. Considering the uncertainty and ambiguity of disaster relief information and using Interval Type-2 Fuzzy Set (IT2TFS), this paper presents a collaborative optimization model based on an integrative emergency material supplier evaluation framework. The optimal emergency material suppliers are first selected using a multi-attribute group decision-making ranking method. Multi-objective fuzzy optimization is then run in three emergency phases: early -, mid-, and late-disaster relief stages. Focusing on a massive flash flood disaster event in Yunnan Province as a case study, a comprehensive numerical analysis tests and validates the developed model. The results revealed that the proposed optimization method can optimize emergency material planning while ensuring that reserve material safety inventory is always maintained at a reasonable level. The presented method suggests a fuzzy interval to prevent emergency materials’ safety inventory shortage and minimize continuous life/property losses in disaster-affected areas.

Keywords: Collaborative fuzzy optimization; Emergency material reserve structure; Disaster relief supply chains; Fuzzy multi-goal decisions (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10479-022-04758-5

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